Amazon Redshift is a data warehouse part of the larger cloud-computing platform Amazon Web Services.
Why Castor x Redshift makes sense?
Redshift is a fast, scalable, and reliable data warehousing service that makes it simple and cost-effective to analyze all your data using standard SQL and your existing business intelligence tools. However, similar to other large-scale data processing tools, pinpointing the most pertinent data assets swiftly and efficiently can be a daunting task. Furthermore, comprehending the lineage between data warehouse tables and other assets like reports or dashboards is not straightforward. Castor, conversely, is engineered to simplify the process of finding the most pertinent data assets with a robust search optimized by popularity and advanced filtering options. Castor also elucidates the lineage between the data warehouse tables and other assets like reports or dashboards. Hence, the integration of Castor with Redshift is logical as it will augment the user experience by facilitating the quick finding of pertinent data assets, understanding their lineage, and ultimately instilling trust and visibility in the data. This, in turn, will empower businesses to make more informed decisions swiftly, which is imperative in today's dynamic world.
How does Castor x Redshift integration work?
Castor ingests metadata from Redshift. This metadata is then transformed and exhibited in Castor. The metadata displayed can include table and column names and descriptions, queries frequently run against your data, frequent users of data assets, data lineage links, data quality tests, last data table update, technical and business tags, and more. Castor organizes this metadata in an intuitive interface that is user-friendly for both technical and business users. The ingestion process is approximately 30 minutes to set up, and the metadata is available in Castor the following day. It is crucial to note that Castor does not access the data itself, only the metadata. This ensures that your data remains safe and secure while Castor delivers as much value as possible.
API Access: if any metadata element is not available in CastorDoc's native integration, you can ingest it with our comprehensive API.
Important: CastorDoc do not access the data itself, only metadata. This ensure that you data stays safe & secure while CastorDoc delivers as much value as possible.
What does CastorDoc help you with?
Castor enables you to scale your self-service analytics strategy without losing control. We are designed with real use-cases in mind :
🔎 You work with data you don't know
Your boss asks to build a report on "Churn for Premium Users in 2021". You need to find the relevant dataset, understand the meaning of its column, and use it fast.
✅ Reduce by 95% the time to find the right data asset (source : Lyft)
🧬 A key employee is leaving
Mike, the data engineer that built the entire data infrastructure is leaving at the end of the month. All the knowledge is in his head. He needs to write it down.
✅ 42% of the work not recovered without knowledge management (source : 360Learning)
👩🏽🌾 A new employee onboarding
Elsa, data analyst, arrived last week. She has no idea what data the company stores or how it is used. She spends hours asking around to gather knowledge.
✅ New hires are autonomous after day 1
💣 A data pipeline is late
Nelson, customer success analyst, refreshes the "daily active users" dashboard every two minutes. The data hasn't arrived yet. He wants to know what is happening.
✅ 5x less Slack messages on #ask_data
🗺️ No one knows where personal information are
Camila, from data governance, has to map all personal information to comply to GDPR requirements. She needs a list of all data assets and their location.
✅ 70% of employees have access to data that they shouldn’t (source)
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“[I like] The easy to use interface and the speed of finding the relevant assets that you're looking for in your database. I also really enjoy the score given to each table, [which] lets you prioritize the results of your queries by how often certain data is used.” - Michal P., Head of Data